Discover how AI and machine learning are revolutionizing the transportation and logistics industry with practical insights, real-world examples, and expert advice from top industry leaders.

In this episode, host Scott W. Luton discusses the impact of AI and machine learning on transportation and logistics with Andersen Yu, Director of Solutions Engineering and Architecture at Front, Ricky Gonzalez, CEO at Hubtek, and Walter Mitchell, CEO at Tai Software. Listeners will learn about the gradual adoption of AI tools in logistics, critical considerations for seamless integration, and the essential role of human involvement in AI processes.

The discussion also tackles common risks, emphasizes the importance of KPIs for tracking effectiveness, and explores how AI can be used for internal and external operational efficiencies. Tune in to gain actionable insights that will help you leverage AI to enhance your supply chain operations.

Narrator [00:00:04]:

Welcome to Supply Chain Now. The voice of global supply chain. Supply Chain Now focuses on the best in the business for our worldwide audience, the people, the technologies, the best practices, and today’s critical issues, the challenges and opportunities. Stay tuned to hear from those making global business happen right here on Supply Chain Now.

Scott W. Luton [00:00:32]:

Hey, hey. Good morning, good afternoon, good evening, wherever you may be. Scott Luton here with you on Supply Chain Now. Folks, we have an excellent show teed up here today. We’re going to be talking all about how AI and machine learning is transforming operations and results, especially when it comes to the world of transportation and logistics. And, folks, we’ve got a trio of business leaders that’s going to be offering up actual insights on how you can up your game. So stay tuned for a great discussion, folks, if you enjoyed today’s show, be sure to share it with a friend or your network. They’ll be glad you did.

Scott W. Luton [00:01:06]:

All right, when I get work. Welcome in our esteemed panel here today, starting with Andersen Yoo, director of solutions, engineering and architecture, with front, followed by Ricky Gonzalez, CEO at Hub tech and backed by Popper Demand, Walter Mitchell, aka Mitch, the CEO at Tai software. All right, Andersen, how you doing?

Andersen Yu [00:01:26]:

Doing good. Hey, Scott, thanks for having me here today.

Scott W. Luton [00:01:29]:

Wonderful to have you here. Ricky Gonzalez. How you doing, Ricky?

Ricky Gonzalez [00:01:32]:

I’m doing fantastic, Scott. Thank you for having me. Excited to be here. Mitch, great to see you again. Happy to share here a lot of information to the public here today.

Scott W. Luton [00:01:42]:

Oh, we’ve got, as I mentioned, we got three folks that bring it here today. And Mitch, welcome back. Great to have you here today.

Walter Mitchell [00:01:52]:

Hey, it’s great to be back. Thanks for having me again. Scott Andersen, Rickey, nice to see you guys again.

Scott W. Luton [00:01:58]:

Here’s where we’re going to start. Andersen, Mitch and Ricky, folks. It’s international axe throwing day. Yes, you heard me right. Axe throwing loggers are said to have made it popular back in the 18 hundreds. And then in the 1940s, you had lumberjack competitions that began. And evidently in the last few years, unbeknownst to me, because I’m not a cool guy, axe throwing has become wildly popular. Bars have popped up that offer lots of axes and targets and beers to me.

Scott W. Luton [00:02:27]:

Beers and axes, well, they don’t seem to mix, but maybe I’m in the minority here. So I want to ask the panel here. And, Andersen, let’s start with you. When you’re hanging out with your friends or family over a cool beverage or an adult beverage, what do y’all like to do? You like to throw axes or there’s something else y’all do when you get together.

Andersen Yu [00:02:44]:

Yeah, we actually. Funny story. We actually have done axe throwing as a company off site activity. I will. I was very bad at it. Um, no beverages needed for that to happen. But for me, no. Definitely hanging out with friends.

Andersen Yu [00:02:58]:

A cold beverage. Love to do it on a golf course. Uh, we’ve got a lot of beautiful golf courses here in San Francisco. So blessed to have that. And, uh, yeah, again, excited to be here, and thanks for the question.

Scott W. Luton [00:03:08]:

Oh, it tell you it’s a phenomenon to axtro is taking over the globe. It is. So, Mitch, I’m coming to you next. When you hang out with friends and family, y’all do some ax throwing or some other things you like to get into.

Walter Mitchell [00:03:18]:

Yeah. Well, similar to Andersen, we did a team building event with axe throwing, and my team put my face up on the. On the dartboard. On the axe board. So I’m not sure what that says about my leadership skills or what, but we’re going to just hope it was all in fun. But personally, I lean a little more towards the dartboard, and a nice evening. Throwing some darts is always a good time.

Scott W. Luton [00:03:41]:

Oh, I love it. We gotta get a picture of you and your team throwing axes at your. Your blown up image on the target. That’s awesome.

Walter Mitchell [00:03:49]:

I’m pretty sure we have one that we can. We can share with you.

Scott W. Luton [00:03:52]:

Share it with us. What a cool thing to do. Get team out and have some fun. So, Ricky, now we gotta tell folks out there. Ricky is tuned in from beautiful Portugal, where the weather is, like, 70 degrees. Food is delicious. But, Ricky, when you’re with friends and family and you’re enjoying the evening over a nice, cool beverage, what do you like to do?

Ricky Gonzalez [00:04:11]:

Well, I think I’m left behind. Unlike my two peers here, I’ve never done axe throwing, and we’ve never done it in the company. I think we need to try that out as a leadership exercise. But when I get with friends and have some beers or wine, I love playing pool or playing a sport that is called tree caram cushion Billard, which is very european and very south american. So it’s, you know, it’s kind of the pool table, but has no, you know, no holes in it. So, you know.

Scott W. Luton [00:04:40]:

Okay.

Ricky Gonzalez [00:04:41]:

Carrom with tricotions, a very, very nice part. So, you know, I like to enjoy it here and there, but never done x throwing. But I gotta try it.

Scott W. Luton [00:04:51]:

All right. We’ll have to all throw. Try our hand at some axe throwing. It seems like Andersen and Mitch may have a leg up on us. We’ll check it out, Ricky, I think we can take them. All right. So folks, we got a lot of good stuff to get into here today. Really very timely topic as well.

Scott W. Luton [00:05:07]:

And we want to start by offering up some really valuable context for audience. We can’t get enough context in this fast moving world we live in. And Ricky, I’m going to stick with you. If you would briefly tell us about what hub tech does and a little bit about your background.

Ricky Gonzalez [00:05:21]:

Most definitely. So I’m Ricky here, CEO at Hub tech. I’ve been in logistics for about 20 years. It’s been a while. I’ve been in different aspects of logistics and supply chain from three PL to MRO distribution, running an asset based operation and now running haptic. So haptic is basically two different businesses, one being talent tech, which is a global talent provider primarily for logistics companies. Then we also have Tabby Connect. And Tabby Connect is a rate management system and using a lot of AI for each application.

Ricky Gonzalez [00:06:01]:

So we help clients gain efficiency and quote freight faster through AI and automation.

Scott W. Luton [00:06:08]:

Love it. And I especially love anything that engages our talent, our valuable talent on teams out there. Good stuff there. Ricky Andersen, come to you next. Tell us briefly about front and your background.

Andersen Yu [00:06:19]:

Yeah, hi everyone. Yeah, Andersen here. I’m the director of solutions engineering and architecture up front. No, it’s a, it’s a long title there but uh, yeah, I’ve been with front for about eight years now. We’ve, we’ve really created this AI email platform that three pls use to manage really all of that chaos that comes with having hundreds of distribution groups. I don’t know any of you in the audience are part of however many distribution groups, but I’m sure when you wake up and your inbox is like absolutely chaotic jam up, that’s the problem that we solve. Um, we eliminate duplicate replies, missed messages, slow responses. Um, and we do that by giving people really easy, no code automation, built in collaboration integrations with tools like Tai.

Andersen Yu [00:07:00]:

Hey Mitch, we were at his conference uh, last week, which is really exciting and we also give you analytics to run your business. So yeah, again, super excited to be here and yeah, really excited for this panel, man.

Scott W. Luton [00:07:11]:

Andersen, we got a chat after this. Good to have you here. And Mitch, great to have you back. We enjoyed a great conversation a month or two ago. Tell us briefly remind some of our audience members about Taie software.

Walter Mitchell [00:07:23]:

Yeah, I’m Walter Mitchell, CEO of Taie software. Tai Software is a transportation management system for the us based freight brokers. We focus specifically on freight brokers, mostly leaning on LTL and full truckload. And the TMS is really focused on how to be operationally excellent.

Andersen Yu [00:07:42]:

Right.

Walter Mitchell [00:07:42]:

So how do we take tools like, like front and, and integrate them into our platform to give an end to end solution that really helps the people doing the job every day, be the best they can do it?

Scott W. Luton [00:07:52]:

Oh, I love that. Empowering the human element to be incredibly successful and making it easier for them to be successful. Good stuff there. Ricky, Mitch and Andersen. Hey, Neil, you’re in the right place. So Neil’s tuned in from Philadelphia via LinkedIn. He says he’s always interested in seeing how AI can be used in new ways. So now that we’ve kind of established some context of our wonderful panel here, we’re going to move into one critical message that our audience has got to take away from this conversation.

Scott W. Luton [00:08:20]:

Right. AI is no longer, it hasn’t been for a long time, around the corner or a nice to have AI is fast becoming table stakes. You can go out and check plenty of research out there. Gartner and lots of other folks have shown how leading organizations are already have been leveraging AI to widen that gap between them and their competitors. Right. So I want to start there. I want to get you all to comment. Right? Because we’re not talking next generation, we’re not talking next month or next year.

Scott W. Luton [00:08:47]:

We’re talking. It’s been here, it’s been here for a while already. Andersen, talk about the opportunity that AI poses.

Andersen Yu [00:08:54]:

Yeah, yeah, I mean, definitely, AI is here. AI is here to stay. Um, I think truthfully, you can kind of say this, like you can say this about any technology. At the end of the day, AI is a tool. It’s a very powerful tool, but it is a tool. And companies that adopt new tools will always have first mover advantage. So companies that adopt AI first over AI’s or companies that don’t, you know, like they’re going to have that advantage over companies that are slow to change. I think in the spirit of building a competitive edge, I think that what’s most interesting to me about AI is not just the power or how dynamic it is, it’s really the speed at which it is evolving.

Andersen Yu [00:09:32]:

Right. So when we think about the competitive edge, the idea that the way that you deploy AI today, which is the way that you gain your competitive edge, could quickly become status quo by a new model that comes out in six months, is just really, really wild. Right. You always have to be looking out for new technology, new ways to adopt things, and in a actually kind world where AI becomes democratized and easily accessible, that competitive edge of swings back to the experience that you create for your end users and your customers. And so kind of building off of what you were talking about, Scott, this, like, human element or, like, accelerating or help. Help supporting your humans and delivering great experiences, I think that is actually where the competition and the competitive edge will end up being over the long run.

Scott W. Luton [00:10:19]:

Love that. And I love how you identify that evolution velocity, right? Cause it tell you, what have you done for me lately? That’s. That’s what a lot of folks are asking AI other technology innovations that Andersen’s kind of talking about, and I don’t know about y’all, Andersen’s a golfer. He just hit a 350 yard drive right down the middle of the fairway. As in this opening commentary, Ricky, speak too broadly. The opportunity that AI poses, most definitely.

Ricky Gonzalez [00:10:46]:

I will start with a challenge and then turn it into an opportunity. Based on recent studies from Gardner and McKinsey, that’s 80% of business leaders think that AI will disrupt their business, but only 20% say they’re ready to take on AI. So there’s a huge gap if you see, but also a huge opportunity to really go and embrace AI, embrace the change. I agree with all of you guys. AI, unlike other technologies like blockchain in 2018, that was a hype and it was kind of in everybody’s mind, AI is here to stay. AI is no longer a nice to have, but a need to have to run your operation because your competitors are doing it.

Scott W. Luton [00:11:34]:

That’s right, Ricky, excellent point. Excellent point. I like the challenge. I love when we come out the gates, challenging our audience to think differently. Good stuff there, Ricky, Mitch, your thoughts, your opening thoughts on the opportunities that AI poses out there?

Walter Mitchell [00:11:48]:

I think these gentlemen said it really well, that AI is no longer something that’s down the road. It’s here today. It’s mature enough that you can see ROi with AI products today. But to what Ricky was talking about, blockchain was hype for a while, and there’s been other technologies that have come and gone. It’s not necessarily just implementing AI for the sake of implementing AI, it’s also. It’s a tool, which is what Andersen was saying, right, then use the tool, or find a way to use the tool to add value to your business. So don’t just try to implement AI for the sake of implementing AI. Look at the power of the tools that are available and see how those tools can impact your business and what you’ll find is the maturity of AI and the rapid iterations that we’re talking about.

Walter Mitchell [00:12:35]:

These things are going to impact your business today, and they can impact your business in really amazing ways right now. So take advantage of that, get that competitive edge going today because it’s ready, it’s here now.

Scott W. Luton [00:12:48]:

Excellent point, Mitch, and I also love what you talked about. Let’s identify the business objective and what we’re looking to do. Our audience out there have heard me say this about a million times, and then let’s find the appropriate solution, the appropriate technology, rather than, as you said, mentioned adopting AI for the sake of adopting AI. Okay, Ricky, Mitch and Andersen, we’ve set the table, I think, very nicely. And now I want to kind of dial it in here on the transportation sector and share a really world, a really practical, real world example of how AI is being leveraged successfully with outcomes, with impact from what you are seeing. So Mitch, why don’t you lead off here.

Walter Mitchell [00:13:28]:

Yeah, so similar line of use. The tool where the tool is valuable is an important component of this. What I mean by that is, for example, EDI and APIs for track and trace on the LTL space have worked really, really well. And that maybe isn’t the best use case for AI. However, the places where AI adds a tremendous amount of value is where you have a little bit more natural language, a little more dynamic processing that needs to happen. So two of the best use cases that I love to talk about is email and documents. So talking about documents, this is where we have an incoming pod. Well, incoming pods can get a little weird, right? Especially you never know what they look like.

Walter Mitchell [00:14:12]:

But we can use AI to reformat the document to take away some of the weird images that happen, make them look more like documents. We can use AI machine learning algorithms to extract the content and intelligently decide what kind of document it is. And the same thing applies to email, where emails are unstructured and we can take that unstructured natural language, the way people write, and turn it into meaningful context that our systems can process and handle intelligently around. So those are two use cases that I really like to talk about in the transportation sector that can add meaningful value today.

Scott W. Luton [00:14:50]:

Yeah, real practical. I think a lot of folks in our audience can relate to those. And documentation, the tidal waves of documentation. I’ve loved to see technology tackle that here in recent years. Andersen, you’re nodding your head. What else would you add to real world examples, especially in transportation?

Andersen Yu [00:15:05]:

Yeah, I mean, Mitch talked about this a little bit, right? Like there is a lot of unstructured data with email. Email is the space that front plays with, and we partner really nicely with Tai in that facilitation of unstructured data to them, and they can process that information. But, you know, AI models, again, really good at making inferences off of unstructured data. And so one of the ways that we’ve seen companies successfully adopt AI is, especially in the context of front, is really using it to classify inbound requests. So you get a lot of emails that come in and you can leverage AI and its large language models to classify conversations into certain buckets and then depending on that classification, to take certain actions. So imagine you have an inbox, it receives all kinds of emails, right? Like anybody can send anything to any email address that you have. So you could get inundated with a ton. So you can think about leveraging front AI tagging capability to identify these conversations when they come in and route them directly to a specific team to prioritize, kind of talking about different types of AI and what we’re talking about specifically.

Andersen Yu [00:16:10]:

But generative is something that we can talk about later on. But, yeah, there’s traditional ML and there’s generative components of AI. I think the world that we have to look at is like, what is the best way to apply it to the problem that you’re looking to solve and the value that you’re wanting to give to customers.

Scott W. Luton [00:16:26]:

So, yeah, and I bet, I bet all three of you all would welcome conversations after today’s session to help dive in a little deeper, is my thought. Well, before I go to Ricky, email is still, we got slack and texting, all this other stuff, but email still makes so much happen. And why not do it better, right? And why not leverage AI and all of its different iterations to make that happen? Ricky, when it comes to practical, real world examples, especially in global supply chain, what comes to your mind?

Ricky Gonzalez [00:16:56]:

Yeah, so supply chain companies, transportation companies, are still full of voice interactions, right, with carriers, shippers, and those interactions can be automated and can be AI infused. So you can put an AI technology like tabby voice or any other, to interact with a carrier based on a track and trace process, or even negotiating a rate, negotiating a load, booking a load. So those interactions that happened before through phone, those can be again automated through AI technology today.

Scott W. Luton [00:17:31]:

Man, just make it happen when we’re sleeping. I love that. Making supply chain happen, making money when we’re sleeping. All right, I want to kind of pivot the conversation a little bit. There’s three broad buckets of AI applications I want to kind of hit all three of these. There’s many others, but there’s three that we want to kind of focus in on. And Mitch, I’m going to come back to you here because I want to talk about internal efficiency. So as business leaders are using, or if they’re evaluating how to implement AI in their operations when it comes to internal efficiency, your thoughts there?

Walter Mitchell [00:18:07]:

The question came up of, like, what are the different types of AI as well? Right? And that’s where Andersen touched on. We have, like, you know, traditional machine learning models. We have generative AI models and so forth. But the way we want to think about a little bit is what is the purpose of the implementation? And that’s where, you know, using AI models to help internal efficiency is one of the great areas to do that. And what that means is, for example, how do you take and improve what your team is doing? So, for example, one of the things that we’re doing at Tai for our own team is around our ticket managing system. We have a bunch of staff members that do tech support and that do onboarding support and so forth. When a customer asks a question, we’re using generative AI to look at our knowledge base, to look at our previous ticket history, and to use the lean on top of some of the large language models that are in existence. And we’re taking all of that to suggest a response for our support team.

Walter Mitchell [00:19:10]:

And then our support team is able to take that response, modify it, review it, make sure it’s okay, and then send that back to the customer. So the goal of this is to help share information amongst our team and give them that information in context to, to the real world situation that they’re dealing with now. Most of the time, we hope that the AI models will be able to have the right answer for them and be ready to go so that the human doesn’t really have to do very much at all, but we still want that person to review it and think about it a little bit and maybe add a little bit of context around it or change the response. So the goal here is to help train our team and give them all that information while not requiring them to go hunt for it.

Scott W. Luton [00:19:54]:

Mitch, I love that the more we can empower all forms of technology and empower our team to make their jobs easier day in and day out. The ripple effect, the critical ripple effect of how that increases and protects and increases the service levels to the customers. Right. And that’s exactly, that’s that force multiplier effect that’s so critical right, Mitchell?

Walter Mitchell [00:20:20]:

Yeah, exactly. And that’s why I love the internal efficiency component of it, too.

Scott W. Luton [00:20:24]:

Right.

Walter Mitchell [00:20:24]:

Is that we are, if we make our team better, it makes it so that they can do their job better. And it’s a common theme, I think, around the AI technologies and so forth, and just actually really in technology in general, because since I’ve been in technology, it’s always been, well, technology is trying to replace people, and that’s not the case at all. What technology is really doing is enhancing us and making us so that we can do our job better. So the term I like to use is that technology or AI isn’t going to replace your job, but the people who use it will. And I think we’ve seen that over the last 20 years, and we’re going to see it with the AI wave as well, that the people who know how to use it are going to excel and the best usage of these tools is going to make us level up and become more operational efficiency.

Scott W. Luton [00:21:10]:

That’s right. Mitch, I love that if you’re new to AI and other innovative technologies, but if you’re willing to learn and then apply what you learn, I’m telling you, you’re gonna have all sorts of new opportunities out there. So don’t fear. Lean in and learn. Yeah. Internal efficiency. I love your perspective there, Ricky. I’m gonna switch gears on you and we’re gonna talk about external efficiencies when it comes to AI.

Scott W. Luton [00:21:33]:

Your thoughts?

Ricky Gonzalez [00:21:34]:

Yeah. So let’s look at the customer facing aspect, right? So people are still scared of you implementing technology, whether if it’s traditional automation or AI customer facing. They kind of fear how the customer will react to the technology, and rightfully so. It’s depending on the implementation, you can have a failed implementation or a good implementation that increases your product’s lovability and usability. One of the things we’re working here in Tavi is a very strong and solid copilot in our tool, where it’s guiding the user throughout the tool, making recommendations of what to do next, next best steps, and getting the context of an interaction on screen. Where is incrementally adding efficiency to the usability of our product, facing our client. Customers are liking it. We’re still in the beta testing of it with some clients.

Ricky Gonzalez [00:22:32]:

And again, there’s this change management aspect of, you know, how will our customers behave with the tool? You know, will they believe in the recommendations? But it’s a process. It’s a process that we’re going through, and I think it’s going to improve the usability of the product.

Scott W. Luton [00:22:50]:

Ricky, excellent comments, and I love that you brought up change management because I think as we move faster and faster, Andersen was talking about that evolution velocity earlier, which I think is critical to recognize. Ricky, as we move faster and faster, I think it puts a greater emphasis and a greater need on both change management and, of course, communication, which is a critical part of change management. So, Ricky, as what I’m hearing you say, as you’re rolling out new, innovative enhancements to how you work with your customers, being able to communicate to your customers, hey, this is what we’re doing. This is why we’re doing it. And this is how you can lean in and how it can benefit your organization more. Is that right, Ricky?

Ricky Gonzalez [00:23:31]:

Absolutely. And like every technology implementation, it has a learning curve, but, you know, you have to go through it and step by step in order to get to the desired destination. So far, you know, our customers are loving, you know, what they’re seeing on the analytics side, and, you know, it’s ripe for disruption. There’s, you know, we’re just starting, right?

Scott W. Luton [00:23:53]:

We are just starting. That is right. What an incredible age we’re in. Um, Andersen, we’re going to, this third bucket we’re going to ask you about is a little different, content creation. How do you see AI playing a role there?

Andersen Yu [00:24:06]:

Yeah. Um, yeah, content creation is. It’s, it’s so funny because I’m thinking about internal efficiency, external efficiency, and then you got, like, concentration. How does this, how does this exist here? It’s actually both the byproduct, but it’s also, uh, a feeding into eternal internal efficiency and external efficiency. And what I mean by that is, right, like, AI, and the value and the power that it can provide internally or externally is dependent on the data set that you have. These are large language models with a lot of data. And the amount of data that it has will help ultimately, like, produce value for customers. And so from an internal efficiency perspective, that the use case that Mitch was kind of speaking to.

Andersen Yu [00:24:46]:

Right, like, you’re accelerating the way that your team can respond back to customers and accurately. It needs to train on something, right. That content is super important externally, when you think about, you know, talking to Amazon or whatever, right? Like they’re using their data and they’re feeding it as a way to deflect. Now, content creation, I think it would be really interesting once we can get into a cyclical world where when there’s a human in the loop and that human is working with AI and they’re collaborating with AI, and that’s feeding back to an engine where it’s actually then learning and evolving and continuing to stay up to date with its own content database. That will be really cool. But of course, like, I think to what Ricky was saying about with his example, like AI, large language models are really good at predicting what is the next word that’s going to come in in this context. And so there’s a ton of use cases that we already see in the market and certainly some plugging in front a little bit here, right, that you can use to, like, let’s say, compose a message. You get a message that comes in, you can use AI to detect and understand what’s going on here, and then with a click of a button, compose a draft.

Andersen Yu [00:25:55]:

You can also use the information that you have to compose other things, like a help center article. Front has a knowledge base and you can use that feed at a couple points and it can then produce this full fledged article. Something that would have taken an hour to do can now take five minutes to do. So, you know, we kind of started getting into the space of ROI, but content creation, really, really amazing opportunity and ground for AI to make an impact.

Scott W. Luton [00:26:21]:

Agreed, Andersen. And you’re reading my mind because we’re going to shift gears over to ROI, but before we do, you’re talking about content creation. I wonder how long it will be before we’re at the Academy Awards and they’re giving an Oscar to an AI platform for creating content that moves us. We’ll see. All right, so let’s talk about real return on investment when it comes to ROI. AI, rather. I’m jumbling my acronyms. Ricky, what’s an example of real ROI that you want to point out?

Ricky Gonzalez [00:26:53]:

Most definitely. So in our case with Tabi, we’ve had many customers that have been able to duplicate or even triple their load count, especially nowadays, where we need to get as many loads as possible and get more revenue. So customers are really, really enjoying the technology and getting the benefits out of it early on. So I think that’s quick RoI that you can calculate with net efficiency gains based on what technology is costing you. And there’s also these aspect of buy versus build. So do you want to wait to really implement something yourself? Start from scratch and add these investment overhead where you can go faster to market and with a vendor like any of the three tools here, and really get faster ROI. There’s also one thing to consider. Speaking of ROI that people usually don’t speak about is the hidden ROI or hidden benefits on the ROI side.

Ricky Gonzalez [00:27:58]:

So employee happiness, customer satisfaction. As I said at the beginning, customers are already working with those providers that are implementing technology to get responses faster, quotes faster, so customers will love you more, will go to your shop more because you’re using technology. So those are hidden costs that you’re not necessarily calculating early on, but you need to add them into the equation to really get true ROI of it enterprise value wise, based on the efficiency gains you’re putting into the table, how much your business is going to be worth, because you’re not only a tech enabled business, but you’re getting more done with less. So those are kind of hidden things that you need to consider when building the case for ROI.

Scott W. Luton [00:28:47]:

Ricky, I love it, man. What a great holistic response, from revenue creation to getting time back. Who would have thought we could get time back and create more time? And then my favorite one that you shared is the impact in enabling more happiness for the team. Less heartburn, right. Taking friction out of our operations. Right. Taking complexity out by leveraging AI and the right AI on the right business problem. Good stuff there, Ricky.

Scott W. Luton [00:29:15]:

Andersen, that’s gonna be tough to beat when it comes to real ROI, when it comes to AI. Your thoughts, Andersen?

Andersen Yu [00:29:20]:

Yeah, you’re going to hear us probably say some very similar frameworks for how we think about ROI. When we think about ROI of AI, you also kind of root it in the way that you’re applying it. And so the ways that we think about applying AI is two ways, deflection and acceleration. Right? So deflection, and we’ve kind of already spoken to both of these, deflection is very straightforward, right. You deploy AI in a way that allows a human to not do something. You calculate how much time you save from deflecting that work, multiply that by how much it costs, like an hourly wage, and then boom, you’ve got a cost savings at the end of the day. Acceleration, also very similar. It’s not as lucrative as a deflection because a human is still part of the loop, but you can still ultimately save time.

Andersen Yu [00:30:07]:

The knowledge base example that I said, 1 hour to now, five minutes, you’ve saved, what, 55 minutes worth of time like that is also money, at least not necessarily back to the business because you’re still paying for that person. But potentially, the way that we think about Roi is not having to hire an army of people to do something.

Scott W. Luton [00:30:25]:

Right.

Andersen Yu [00:30:25]:

You can superpower one person to do so much more. Now, just very quickly, I think if you save 30 seconds writing a message and you save 30 seconds from having to catch up on a long thread. You multiply all of that messages, send messages ready across your entire organization, across a year, with your hundreds of distribution lists. Like you’re saving hundreds, if not thousands of hours. And I think that’s super important. And the last thing is that kind of hidden Roi. This is a really interesting one. Cause when we talk about ROI and selling front technology to customers, and they’re like, oh, what’s Roi? Of AI, there’s this idea of the instant Roi, the instant gratification that comes with, oh, deflection.

Andersen Yu [00:31:06]:

It worked. But we all know we’ve talked to. I won’t say any names. Cause, you know, I don’t wanna get banned. Like, companies who then over rotate on a pure deflection strategy with no human in the loop. You can end up in a place where customers are just giving up. Right, like I’ve given up. It doesn’t mean that you’ve resolved my requests.

Andersen Yu [00:31:26]:

It doesn’t mean that, like, you’ve given me value. In fact, you might have given me negative value, but you won’t actually recognize that until the long term. Until the long term when we’re actually renewing the customer. And they’re like, you’ve created a really negative experience for me. And so we have to start to think about Roi, not just in this instant perspective, but in the long run. And at the end of the day, this comes back to the experience that you’re going to create to your customers. It has to be holistic. Yeah.

Andersen Yu [00:31:52]:

And so that. That’s my take on Roi for you all today.

Scott W. Luton [00:31:57]:

Andersen, I love it. And coming to you next, Mitch. I love how Ricky and Andersen both spoke about the hidden Roi. I think a lot of us here out across industry can. Can think about more well known return examples of return on investment. But I love these hidden Roi observations that we focus on here. Mitch, when it comes to ROI, what are your thoughts?

Walter Mitchell [00:32:19]:

Yeah, well said, gentlemen. I think they said it very, very well. And all of their points are absolutely critical to it. I would add on to this, the. A little more practical side of it, kind of what you were alluding to is don’t forget as well that you do need to measure. And KPI’s just for your business as a whole. And we see it pretty frequently in brokerages where they just aren’t really measuring. And if you ask some questions, like how many shipments per day can your dispatchers handle? Or the brokers in your business handle, these kinds of questions are things that you should know about your business ahead of time.

Walter Mitchell [00:32:57]:

So if you are going to measure KPI’s for or ROI for the AI side or anything that you’re implementing, any tool you’re implementing, really you need to measure ahead of time as well as after. Right. So an example of that was one I just use is how many shipments per day does your brokerage handle? What are your average margins? That one everybody should hopefully know, right. Total number of shipments per customer, things like this, like get the KPI’s that matter to your business, get those cemented and down today and run those all the time. Then when you implement any tool, whether it’s an AI tool for internal efficiency, for external efficiency, whatever it might be, that you’re making sure that you understand your business and the KPI’s around your business. So these tools should impact that in a positive way as you come around to the other side and you’ll see then even a KPI should be around employee retention, right. I mean, we should know what percentage of employee turnover we have as a business, especially as our businesses get larger that number and that becomes even more relevant. So let’s know that ahead of time and look at it a year later after we implement these tools.

Walter Mitchell [00:34:07]:

And then we’ll get capture some of those soft benefits around some of the more strategic benefits as well. So you can see all of it, but make sure you’re measuring your business and looking, looking at your business from some of the factors that impact it daily.

Scott W. Luton [00:34:24]:

Yeah, good stuff there. Mitch, would you say so it’s a timeless truth and best practice for business leaders to know their business. But as you’re sharing your perspective there, to me it’s like, gosh, if we want to really take advantage of this modern technological era that we’re in and all that, the benefits that come with it, we better know our business even more so than in past generations. Mitch, would you agree with that?

Walter Mitchell [00:34:51]:

Yeah, absolutely. And then one of the key things that we tend to talk about a lot on this is when you are measuring something about your business, make sure you’re measuring for a business outcome. So don’t measure something just for the sake of measuring it. Measure something because there’s something that brings value to your business. So, like, employee retention is a really great thing to measure because employee turnover is very costly to the business. That doesn’t mean you should never terminate somebody or never have any changes. But what it means is are we focusing on building a company that our customer, that our employees want to be at and measuring that because we care about the outcome of that result same thing applies. Margin on our shipments is really easy because we all care about margin, but make sure we’re measuring things that impact the business in the way we want to impact it.

Scott W. Luton [00:35:42]:

Mitch, good stuff. Good stuff there. And I love how all three of you are offering advice because we’re going there next. Inevitably, there are business leaders out there watching or listening, some that have already started their journey. They’re already maybe having some powerful outcomes as it relates to AI. Or on the other end of the spectrum, some folks are still figuring out how to get started. And that’s where I want to pick y’all’s brain next. So, Andersen, your thoughts?

Andersen Yu [00:36:08]:

Yeah, this is, this is a good one. I’m trying to think, like, is there something like super snappy, super revolutionary that we should be saying here? But I think at the end of the day, and maybe the gentleman in the panel will agree as well, like, think of AI as a tool, and then now you won’t overthink the problem of how to get started. Like, don’t be paralyzed by this technology because it’s a tool like any other tool. Yes, it’s probably evolving quicker, so maybe your strategy needs to be a little bit different. But the, the core approach on how you think about getting started to solve any problem is to one, just identify the problem.

Scott W. Luton [00:36:42]:

Right.

Andersen Yu [00:36:42]:

Like start with the existing problems that you have in your business. I like Mitch’s point about being outcome driven, and you definitely should do that. And you need to, you know, look at technologies that can help you either establish that benchmark if you’re unable to do that today, because that benchmark is super important. And the continuous kind of measuring against benchmark is also very important if you want to assess success with any technology, especially something like AI. But yeah, start with the existing problems that you have within your business. There are also opportunities outside of your business that you can get into. But again, kind of look in your own backyard. There’s probably a ton of things that you are doing routinely that you probably can think about, hey, like we could probably do this faster.

Andersen Yu [00:37:23]:

Anything that, you know, super manual, really. AI, there’s been a lot of evolution and a lot of new technology that can already do so much of this work. So, I mean, ultimately plugging friend a little bit more like the email use case comes to mind. There’s so, so much that we all do in our inbox day to day that has just become the way that we operated with email over the last 20 years. That is a really great place to start as well. Right. And I think that change management does come into play here. So it really important for the leaders to be bought in on why are we doing this? And making sure that message is super clear to your team.

Andersen Yu [00:38:00]:

Because creating that space for innovation will really multiply, like the productivity, the potential outcomes that can come because you’re seeing it here. There’s so many people here that can think and see different, you know, things from different perspectives. So, yeah, I love that.

Scott W. Luton [00:38:16]:

And I love one element of what you shared there, folks. We can’t create enough email rules to keep up with all the different way your channels and all the different messages we’re getting. We gotta lean on technology in a better way. All right, Mitch, advice for business leaders and their teams on how to get started. Your thoughts?

Walter Mitchell [00:38:35]:

Yeah, so it’s about just taking a bite, right? And I think it’s that eat the elephant analogy. Like, how do you do it one bite at a time? Don’t get panicked. As Andersen was saying about the fact that it’s AI, but go ahead and look into what tools are available in the market, and then when you look at those tools that are available, would those impact my business in a good way? And if the answer is yes, then go ahead and implement just that tool. And some of these tools can be implemented in just a few weeks. So it’s not a monumental shift that you have to do to get that in place. Like for example, for a thai user to process documents and start auto processing, bols, pods, carrier bills, you can get this turned on in a matter of a couple hours. And then training your team may take a little bit more time, but this is something that you could do right now and take advantage of. And the cost is almost, almost zero.

Walter Mitchell [00:39:32]:

So it becomes a very easy thing to take one step into and solve one problem. And then when that works, go take another bite, find another problem, solve that problem. But you don’t have to rebuild your entire infrastructure to implement AI functionality and AI tools. Just take it one bite at a time and you’re going to see some big benefits. After you’ve taken probably just one byte, but after you take seven to ten, you’re really going to start noticing something amazing.

Scott W. Luton [00:40:01]:

I love it. Mitch, you’re making me hungry. All right, so Ricky, what other advice would you offer for folks that are getting started?

Ricky Gonzalez [00:40:08]:

Well, great points, gentlemen. I think I can only summarize a good implementation of AI or technology. So four things. So start slow, grab the low hanging fruit, start with, as Andersen said, with what creates the most impact quicker in the organization. That’s the first thing. Second thing will be have the human in the loop in the process. So making sure that the human is either controlling, revising, making sure that the AI outcome is the best outcome and it’s accurate data that you’re interacting with. The third thing will be get the buy in from your champions.

Ricky Gonzalez [00:40:48]:

Identify some champions in the organization that will help you get the implementation through, because we’ve seen that one of the challenges, or the biggest challenges and what drives the biggest failures in AI implementation is the people, the internal teams, even though it’s going to help them in the long run, they fear the technology. So they’ll be, you need to have champions internally. Right. There’s this study out there that says 38% to 40% of jobs are going to be replaced by AI, but also more than 50% of jobs will change because of AI. So this is another revolution that as leaders, we need to embrace and we need to kind of get the organization’s buy in and the organization flowing towards implementing AI. The fourth thing, and I think it’s important, you already have systems in place, you already have workflows in place. Make sure the AI integrates with those. Don’t implement AI in a silo because it won’t work.

Ricky Gonzalez [00:41:52]:

It will fail in the short, mid and long term.

Scott W. Luton [00:41:56]:

Wonderful. I love your four item checklist there. And, you know, I’ll just add to the jobs being eliminated, jobs being changed. There’s tons and tons of jobs also, as all three of you all know, being created, right. And in fact, study after study will point to that modern technology will create a whole bunch more jobs than the jobs that may be eliminated. All right, let’s talk about risks. Actually, we’re talking about some risks already, right? Because the mindset and the psyche of our, of our team is really critical, and that’s a risk if we don’t navigate it better. Mitch, I’m going to come back to you first here.

Scott W. Luton [00:42:30]:

Risks that should be understood when it comes to AI adoption, especially related to logistics operations. Mitch?

Walter Mitchell [00:42:38]:

Yeah. I think communicate with your team and make sure your team knows that these tools are here to make you better at your job, not eliminate you from your job. I think that’s an important thing to talk about, but also don’t let the resistance overcome the progress. So it’s easy to say that, well, we don’t want to take these risks or we can’t take these risks and stop for the sake of saying we’re not willing to take a step forward. But that’s always going to be the case when change is here, we have to push through that. Now you have things like governance, privacy, security concerns with AI and with any tool we implement. These are super important things you shouldn’t take lightly. However, the answers are there, the solutions exist, so they’re not reasons to stop an AI implementation, the reasons to be thoughtful about an AI implementation, or any tool for that matter.

Walter Mitchell [00:43:31]:

So don’t let those things prevent you from moving forward, but be aware of those risks as you take that first step. And then another thing to Ricky’s point, the human in the loop, that’s probably where you have the biggest risk, is if you try to implement something where you’re eliminating your staff from the process or eliminating the human in the loop. I like to use the term that I borrowed from somebody else called human on the loop instead of human in the loop. And I think that’s a great term to demonstrate AI, because we want to let the human still be involved in it and supervise what our tool is doing at a faster pace. And that’s the goal. So don’t try to implement something where we’re expecting everything to happen perfectly, but if we can reduce what we’re doing by 50%, that’s a tremendous win.

Scott W. Luton [00:44:19]:

That’s right.

Walter Mitchell [00:44:20]:

That’s a tremendous benefit. So go ahead and tackle it from that point of view and understand the expectations as you jump into this new world.

Scott W. Luton [00:44:28]:

Excellent point there, Mitch. Several of them, Ricky, risks what comes to your mind?

Ricky Gonzalez [00:44:33]:

Yeah. So I think now that Mitch mentioned the people aspect, which I think is the biggest risk when considering failed automations or failed implementations, I think is the data itself, what kind of data you’re interacting with, is it biased? How did you train or how your vendor trained the model that you’re interacting with? So the data itself becomes super important to determinate the success or the failure of the AI implementation.

Scott W. Luton [00:45:07]:

Yep. Excellent call out there, Andersen. Risks.

Andersen Yu [00:45:10]:

Yeah, I think it’s super tempting to see AI as that silver bullet solution, but as we all know, there are pitfalls when it comes to AI, like hallucinations. I’m sure we are all on the Twitter sphere or sorry X or LinkedIn, and you see things like, my favorite one is when Google was rolling out that, like, AI contact card, that there was one that said, like, not only is it not dangerous, but you should stare at the sun for like five to ten minutes every day. And that was just like, it was so good, right? So, like, again, this is already happening outside the logistics operations world, but people are still coming to terms with, like, how does this work for us. Really. I’m going to, I’m going to take that one. The human on the loop when it comes to adoption, really in favor of coming up with an approach that isn’t purely just deflective, but keeping that human on the loop approach. Um, let humans do what humans are really good at. Make informed decisions.

Andersen Yu [00:46:08]:

Let AI surface information to humans so they can make those decisions faster.

Scott W. Luton [00:46:13]:

That’s right. Better decisions, more confident decisions. The right decisions. Faster. Good stuff there, Andersen. Speaking of faster, we’re going to have a fast and furious finish. We’ve got a lot to get in the last ten minutes or so. And I will start with each of your one piece of advice for selecting the right partner to help with AI implementation.

Scott W. Luton [00:46:33]:

And, Ricky, let’s go with you first.

Ricky Gonzalez [00:46:35]:

So I might be biased to answer this, of course, I’m a technology provider here, but I think choose the one provider that has the experience, that connects with your vision, connects with your business goals, and that knows how to do it right. So don’t go just with anyone. Don’t go with just with price. You know, take the time. Take the time to identify, you know, previous successes from your vendor. You know, get a lot of references out there, talk to a lot of people before choosing the right partner to, you know, help you through this journey. I think that’s super important. Connecting with your business goals is paramount to really, you know, make sure that the implementation goes smooth and you’re helping your clients quickly enough.

Ricky Gonzalez [00:47:21]:

Right. And getting the ROi quickly enough.

Scott W. Luton [00:47:24]:

Excellent point, Ricky. The art of the possible is nice. Right. But more important to Ricky’s point, ask what they’ve done right where. Where they’ve applied all their bells and whistles and the outcomes they have already achieved. That’s really, really important. Mitch, your thoughts when it comes to one piece of advice for selecting that right partner.

Walter Mitchell [00:47:44]:

Yeah, I think Ricky nailed it right there. It’s about finding a partner who has experience in a specific area that you’re looking for. So, for example, you know, make sure that the provider that you’re talking to understands your business and understands your use case really well. And if they understand that really well, then get on in there. References, testimonials, all super important pieces of that to make sure that you’re working with a partner that’s going to support your business objectives.

Ricky Gonzalez [00:48:13]:

Yep.

Scott W. Luton [00:48:14]:

Well said. Mitch. Get on in there, do your homework and jump in with both feet. Andersen, your thoughts?

Andersen Yu [00:48:20]:

Yeah, echo everything the other folks have already said, but I think my take is there’s a lot of AI tools. Again, at the end of the day, it’s all about what is the experience that you want to give to your customers and making sure that as you’re selecting the right partner, the way that they think and approach AI and the value that they see AI, uh, giving to their customers is. Is aligned with yours.

Scott W. Luton [00:48:42]:

Right.

Andersen Yu [00:48:42]:

Like, if you’re really. If you really care about a human on the loop approach, don’t look for a partner whose goal is to completely deflect, because they’re not going to work on the things that really are focused on the thing that you care about. So, you know, think about the values, like, understand where, what is their approach, how are they thinking about innovation? Um, and, like, how much you’re dedicating to it. But yes, all the other things are really great. Use case testimonials. Do it all.

Scott W. Luton [00:49:09]:

But, yeah, so. And just because someone might add AI to the outside of some really slick packaging, it looks really cool. Ask the questions. Get down to the nitty gritty of where and how they’re leveraging real powerful AI that’s going to make a big difference. Don’t go for the. Don’t go for the slick marketing. All right, so a lot of good stuff here. I’ll tell you.

Scott W. Luton [00:49:32]:

I wish we had a couple more hours. But the good news is folks can reach out and connect with our panel and have conversations over axe throwing or beverages or you name it, our billiards, as Ricky was talking about. Being able to fostering those connections is wonderful here. And I want to start with you or stay with you, Andersen, how can folks connect with you and the team over at front?

Andersen Yu [00:49:54]:

Yeah, you can add me on LinkedIn. You can find us@front.com dot. And, yeah, super excited to connect with anyone here in this space who wants to talk about AI, wants to talk about email. Been talking about email for eight years now. So lots of learnings, lots of trials, lots of tribulations. But, yeah, excited, excited for all of you to have been here today. Thank you again for. For having me, Scott.

Scott W. Luton [00:50:17]:

And, yeah, Andersen, I would just add y’all. Y’all haven’t been talking about it for eight years. Y’all been really doing stuff and making a massive impact over the front team. So front.com, next up. Hey, Ricky, how can folks connect with you and the hub tech team, all the cool things you all got going on over there?

Ricky Gonzalez [00:50:35]:

Yeah, same thing, LinkedIn, Ricky Gonzalez. But also reach out through the website, any of our two divisions. So go to gohubte.com and reach out to any of the two reps either. Tavi, connect for the rate automation management system and then go talenttech.com for the global talent peace.

Scott W. Luton [00:50:59]:

It’s just that easy. And we got it. We got a magical easy button on our end, too. We’ve got Ricky’s LinkedIn, right? And my hunch is we’ll have Mitch’s too. Mitch, really appreciate your leadership and bringing this conversation together, connecting us with the dynamos that are Ricky and Andersen. How can folks connect with you, Mitch and the powerful tie software team.

Walter Mitchell [00:51:18]:

Yeah, you can reach Tai software on LinkedIn through thai software. You can reach me on LinkedIn as well. You can also reach us@tysoftware.com but again, pleasure to be on the show with you and we look forward to making more connections. I hope everybody today got something valuable and is able to take that first bite towards some improvements using AI.

Scott W. Luton [00:51:39]:

No doubt. Mitch and I really appreciate the kind of different angles. All three of you all came at this for a really holistic conversation. But folks, wait, there’s more. Mitch, I’ll tell you, as he talks, it’s like he just kind of creates a serenity. And we need more serenity in global supply chain, right? Check out what Tai is up to. And we encourage you. Don’t just take our word for it.

Scott W. Luton [00:52:00]:

Hey, kick the tires, challenge them, book a demo. Really enjoyed our conversation here today. I learned a ton. Appreciate the education. Hey, are you all offering a certification? Because I think that’s what we’ve gained here today. Really have enjoyed it. Andersen Yu, director of solutions engineering, architecture with front. Thanks for being here, Andersen.

Scott W. Luton [00:52:20]:

Ricky Gonzalez, CEO at Hub tech and then some. Please enjoy beautiful Portugal. And Ricky, thanks so much for being here.

Ricky Gonzalez [00:52:27]:

Thanks for inviting me. It was great.

Scott W. Luton [00:52:29]:

You bet. Walter Mitchell, aka Mitch, great to have you here. Really enjoy what you and the team and your role CEO at TA software, really appreciate what you are doing and looking forward to reconnecting again with you soon.

Walter Mitchell [00:52:42]:

Thanks again for having us. Appreciate it.

Scott W. Luton [00:52:44]:

You bet. All right, folks, now you’ve heard from Ricky and Mitch and Andersen, all sorts of powerful and actionable perspective, right? But now the onus on y’all, if you’re listening, if you’re watching on us, on you to take something they’ve shared here today and put it into action. Cause your teams, they’re craving better ways of doing things. They want to change how business is done. They want to be more successful. And you as leaders, we got to help facilitate that. All right? It’s our responsibility. So on behalf our entire team here at Supply Chain Now.

Scott W. Luton [00:53:13]:

Scott Luton, challenge. You do good, give forward, be the change that’s needed. We’ll see you next time. Right back here at Supply Chain Now. Thanks for buying.

Narrator [00:53:23]:

Thanks for being a part of our Supply Chain Now community. Check out all of our programming at SupplyChainNow.com and make sure you subscribe to Supply Chain Now anywhere you listen to podcasts and follow us on Facebook, LinkedIn, Twitter and Instagram. See you next time on Supply Chain Now.